Analysis on Location Based Nearest Keyword Search
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 2
Abstract
It is common that the objects in a spatial database (e.g., restaurants) are associated with keywords to indicate their businesses/services. An exciting problem known as Closest Keywords search is to query objects, called nearest keyword search , which together cover a set of query keywords and have the minimum inter-objects distance. Observation is the increasing availability and rank of keyword rating in object calculation for the better decision making. This inspires us to study a generic version of Closest Keywords search called Best Keyword Cover which considers inter-objects distance and the keyword rating of objects. The baseline algorithm is inspired by the methods of Closest Keywords search which is based on fully combining objects from different query keywords to generate candidate keyword covers. When the number of query keywords increases, the performance of the baseline algorithm falls melodramatically as a result of massive candidate keyword covers generated. To recover this weakness, this work proposes a much more scalable algorithm called keyword nearest neighbor expansion (keywordNNE). keyword-NNE algorithm meaningfully reduces the number of candidate keyword covers generated. The in-depth analysis and general experiments on real data sets have correct the advantage of our keyword-NNE algorithm.
Authors and Affiliations
Miss Rachana V. Kurhekar, Prof. R. R. Shelke
Keywords
Related Articles
- EP ID EP23130
- DOI http://doi.org/10.22214/ijraset.2017.2041
- Views 229
- Downloads 5
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